{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "7546cfc6acbb4e0cbd4bd6829788e57a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_b4d943d7667943dd8fd1e408a3a52279",
              "IPY_MODEL_7afe045dcc7c448996c5013e3e622974",
              "IPY_MODEL_fe45fd6fc8e445169a620d616dcf2e22"
            ],
            "layout": "IPY_MODEL_3c88c87b6d70467cb65f006aab476f2a"
          }
        },
        "b4d943d7667943dd8fd1e408a3a52279": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c3af5e78a13347dbbe9644a4f1a6f105",
            "placeholder": "​",
            "style": "IPY_MODEL_898f94dd2f2242a684685b4258019158",
            "value": "Downloading (…)lve/main/config.json: 100%"
          }
        },
        "7afe045dcc7c448996c5013e3e622974": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_2e8cce8884254ae890718ed83d37ecca",
            "max": 4186,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_a1d51ddcfff849829f12a2a4f3dba3ea",
            "value": 4186
          }
        },
        "fe45fd6fc8e445169a620d616dcf2e22": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a25fefe1645b4211a312c4de0111b320",
            "placeholder": "​",
            "style": "IPY_MODEL_2afc0f34505940e88dd9792ccb0bdc50",
            "value": " 4.19k/4.19k [00:00&lt;00:00, 123kB/s]"
          }
        },
        "3c88c87b6d70467cb65f006aab476f2a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c3af5e78a13347dbbe9644a4f1a6f105": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "898f94dd2f2242a684685b4258019158": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "2e8cce8884254ae890718ed83d37ecca": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a1d51ddcfff849829f12a2a4f3dba3ea": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "a25fefe1645b4211a312c4de0111b320": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "2afc0f34505940e88dd9792ccb0bdc50": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "7e2a19c580444d788fe46680e412d327": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_b17b630a30424ebbb442c26cc20952c5",
              "IPY_MODEL_30a9bba5a18246239c8ca14b054bc303",
              "IPY_MODEL_d72d87cf51264d34b51942aa6b003a68"
            ],
            "layout": "IPY_MODEL_6b9eb0faae80483a8741c4faad9a6171"
          }
        },
        "b17b630a30424ebbb442c26cc20952c5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4de0e43af4b143c1bdbc0df06ea96a71",
            "placeholder": "​",
            "style": "IPY_MODEL_dd631ece54c143998dec7795f7488bf4",
            "value": "Downloading tf_model.h5: 100%"
          }
        },
        "30a9bba5a18246239c8ca14b054bc303": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_49011a6dcc9941999a09ee6ce3ab6959",
            "max": 605551040,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_3323249fd8de42939ed6a9ef32633dce",
            "value": 605551040
          }
        },
        "d72d87cf51264d34b51942aa6b003a68": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_14c2cd27faab4a58850784701f048726",
            "placeholder": "​",
            "style": "IPY_MODEL_008e2c6b85534ee18f72997820e075c2",
            "value": " 606M/606M [00:05&lt;00:00, 127MB/s]"
          }
        },
        "6b9eb0faae80483a8741c4faad9a6171": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "4de0e43af4b143c1bdbc0df06ea96a71": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "dd631ece54c143998dec7795f7488bf4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "49011a6dcc9941999a09ee6ce3ab6959": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3323249fd8de42939ed6a9ef32633dce": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "14c2cd27faab4a58850784701f048726": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "008e2c6b85534ee18f72997820e075c2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "b1cf31daa3eb4fdcb2094a08e68f7410": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_ee116dc2cf474c6f94e666acec9f4057",
              "IPY_MODEL_00e2937be48f4d9793745ccaa813f2b9",
              "IPY_MODEL_6c22daabed4c483aaf07d92ee94c3c26"
            ],
            "layout": "IPY_MODEL_8fd80268a2b34249ba4cee9bdba0c3b7"
          }
        },
        "ee116dc2cf474c6f94e666acec9f4057": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_15b05ce1c1434a0c9f23e055f54603f2",
            "placeholder": "​",
            "style": "IPY_MODEL_3e03bc4ff1664bb8802004c301e018cb",
            "value": "Downloading (…)rocessor_config.json: 100%"
          }
        },
        "00e2937be48f4d9793745ccaa813f2b9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_3b6b316b8edf4adb8ea8865c8c09e24b",
            "max": 316,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_953fcb8bdb214b009d939c3d17b4c82a",
            "value": 316
          }
        },
        "6c22daabed4c483aaf07d92ee94c3c26": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ae6bcc2999d64895b9885f03d626c66e",
            "placeholder": "​",
            "style": "IPY_MODEL_d6a75fda819e4db5a584479e6746d97c",
            "value": " 316/316 [00:00&lt;00:00, 20.2kB/s]"
          }
        },
        "8fd80268a2b34249ba4cee9bdba0c3b7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "15b05ce1c1434a0c9f23e055f54603f2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3e03bc4ff1664bb8802004c301e018cb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "3b6b316b8edf4adb8ea8865c8c09e24b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "953fcb8bdb214b009d939c3d17b4c82a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "ae6bcc2999d64895b9885f03d626c66e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "d6a75fda819e4db5a584479e6746d97c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "dfcda88772164b9baa3060bd6a791df2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_d7b341c6d2d144288869d7ca9236ece9",
              "IPY_MODEL_290337b217b6484a943c45258789acb1",
              "IPY_MODEL_88bfa71f30084a20ae32077bd0d0dadb"
            ],
            "layout": "IPY_MODEL_9a2dbcec8fbb4d2dbc0401b06aa6faff"
          }
        },
        "d7b341c6d2d144288869d7ca9236ece9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_fba2735b9f4742d9ae1c07c930224c57",
            "placeholder": "​",
            "style": "IPY_MODEL_739788184eb5483dbc146d6fbd7beb2a",
            "value": "Downloading (…)okenizer_config.json: 100%"
          }
        },
        "290337b217b6484a943c45258789acb1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_490dc51f9c0f4a12941908deaff3e3b0",
            "max": 568,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_dc88cfb1726e4671b314797fc911190b",
            "value": 568
          }
        },
        "88bfa71f30084a20ae32077bd0d0dadb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_f976b427f2494798ae4c658c0dee5916",
            "placeholder": "​",
            "style": "IPY_MODEL_633d4a94b7ef4894b80aa3304aa5dcd2",
            "value": " 568/568 [00:00&lt;00:00, 33.5kB/s]"
          }
        },
        "9a2dbcec8fbb4d2dbc0401b06aa6faff": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "fba2735b9f4742d9ae1c07c930224c57": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "739788184eb5483dbc146d6fbd7beb2a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "490dc51f9c0f4a12941908deaff3e3b0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "dc88cfb1726e4671b314797fc911190b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "f976b427f2494798ae4c658c0dee5916": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "633d4a94b7ef4894b80aa3304aa5dcd2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "75efa71e777843e8848b88ea5989fdeb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_d0c8a50b8da9488d8572f2afaef74845",
              "IPY_MODEL_32fd9d71187a433daa2aef69fbc7812d",
              "IPY_MODEL_aa22f883f356489b8dcc16d080d746d1"
            ],
            "layout": "IPY_MODEL_7c692a6deab84b2d93731ceed4c18d30"
          }
        },
        "d0c8a50b8da9488d8572f2afaef74845": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e68733b158154115a6c326ae7d5280c7",
            "placeholder": "​",
            "style": "IPY_MODEL_2e1289127a324246b79bf1dc598f96de",
            "value": "Downloading (…)olve/main/vocab.json: 100%"
          }
        },
        "32fd9d71187a433daa2aef69fbc7812d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_2b8a81234e2e4763929fc5e7c4663dec",
            "max": 862328,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_ea4bf1a7c2cc47a193daec0ecbbfa37d",
            "value": 862328
          }
        },
        "aa22f883f356489b8dcc16d080d746d1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1c4681c44ddd4b599609eceb0daebda8",
            "placeholder": "​",
            "style": "IPY_MODEL_41d3e17640134324b48236469eba3525",
            "value": " 862k/862k [00:00&lt;00:00, 13.3MB/s]"
          }
        },
        "7c692a6deab84b2d93731ceed4c18d30": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e68733b158154115a6c326ae7d5280c7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "2e1289127a324246b79bf1dc598f96de": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "2b8a81234e2e4763929fc5e7c4663dec": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ea4bf1a7c2cc47a193daec0ecbbfa37d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "1c4681c44ddd4b599609eceb0daebda8": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "41d3e17640134324b48236469eba3525": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "de55938608d04b029d9f93d51e4d8469": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_b250ea671cfb4606893c58cbd213fb84",
              "IPY_MODEL_dbcf83b0aa4648c49b36dab14b0282cb",
              "IPY_MODEL_42f99a181d924563ad237a524e984d73"
            ],
            "layout": "IPY_MODEL_49414e423d3e4729971587a5bd78722e"
          }
        },
        "b250ea671cfb4606893c58cbd213fb84": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c8c99779d4e9435e80662de03a4e6e8e",
            "placeholder": "​",
            "style": "IPY_MODEL_0421441fd7eb49c09a6abd97b019ede6",
            "value": "Downloading (…)olve/main/merges.txt: 100%"
          }
        },
        "dbcf83b0aa4648c49b36dab14b0282cb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a034afb5fbce44629f32454757ad581a",
            "max": 524657,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_f555ec3a64024344b2a843fedd247ae3",
            "value": 524657
          }
        },
        "42f99a181d924563ad237a524e984d73": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_26d3af4d6f9041928887c8ffff9b1b86",
            "placeholder": "​",
            "style": "IPY_MODEL_7fe82c4b486b4bafa6b22abdd70dc8d7",
            "value": " 525k/525k [00:00&lt;00:00, 23.9MB/s]"
          }
        },
        "49414e423d3e4729971587a5bd78722e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c8c99779d4e9435e80662de03a4e6e8e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "0421441fd7eb49c09a6abd97b019ede6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a034afb5fbce44629f32454757ad581a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f555ec3a64024344b2a843fedd247ae3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "26d3af4d6f9041928887c8ffff9b1b86": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7fe82c4b486b4bafa6b22abdd70dc8d7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "020b4b14cddb438d8826a7f4f4b5e57d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_a4a2e7380eea4ffaa9ef6b40817167e8",
              "IPY_MODEL_7a936dfe9461481cacea30d3cef7e50f",
              "IPY_MODEL_66c6a9ba5988443e8a36cc1caa51a330"
            ],
            "layout": "IPY_MODEL_b52fa027a7874e4c8007ad9e78e66cba"
          }
        },
        "a4a2e7380eea4ffaa9ef6b40817167e8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_711f8ac932d84822be4b53d7b297f7f4",
            "placeholder": "​",
            "style": "IPY_MODEL_5383e3b1a42242caa0a004f27a7ebf96",
            "value": "Downloading (…)/main/tokenizer.json: 100%"
          }
        },
        "7a936dfe9461481cacea30d3cef7e50f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_dcc077483bd44aca82bd3882d731a8ae",
            "max": 2224041,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_8d1484f2aa8343758e71d748ddedc650",
            "value": 2224041
          }
        },
        "66c6a9ba5988443e8a36cc1caa51a330": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_50b2b3ef063a4415b1e02c83c4660c6f",
            "placeholder": "​",
            "style": "IPY_MODEL_76198e2a893842d4b46d223916f93ec8",
            "value": " 2.22M/2.22M [00:00&lt;00:00, 39.4MB/s]"
          }
        },
        "b52fa027a7874e4c8007ad9e78e66cba": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "711f8ac932d84822be4b53d7b297f7f4": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "5383e3b1a42242caa0a004f27a7ebf96": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "dcc077483bd44aca82bd3882d731a8ae": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8d1484f2aa8343758e71d748ddedc650": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "50b2b3ef063a4415b1e02c83c4660c6f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "76198e2a893842d4b46d223916f93ec8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "4e98f7f6f7e6487db77d66f57e02c7e1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_0efc18133e6a4cceb6b2563353677d88",
              "IPY_MODEL_714837a4a3ad4c3386d1acc2e8d56363",
              "IPY_MODEL_129d1b2227b94cbeabccff23398337ce"
            ],
            "layout": "IPY_MODEL_eeba9e0435534a1ca647ce5240b3aaf7"
          }
        },
        "0efc18133e6a4cceb6b2563353677d88": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_3a89d19646cb4b0e9b3ec73515701446",
            "placeholder": "​",
            "style": "IPY_MODEL_650502808486475a9ea393ddbcd95891",
            "value": "Downloading (…)cial_tokens_map.json: 100%"
          }
        },
        "714837a4a3ad4c3386d1acc2e8d56363": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_46500824ea734f999df671de062437fb",
            "max": 389,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_f3663995cddb48f2989a07d15891bf5e",
            "value": 389
          }
        },
        "129d1b2227b94cbeabccff23398337ce": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4d9e512aa24c4f16a979b2aae359800c",
            "placeholder": "​",
            "style": "IPY_MODEL_f20b711c4f044879b75087426f938f53",
            "value": " 389/389 [00:00&lt;00:00, 15.0kB/s]"
          }
        },
        "eeba9e0435534a1ca647ce5240b3aaf7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3a89d19646cb4b0e9b3ec73515701446": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "650502808486475a9ea393ddbcd95891": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "46500824ea734f999df671de062437fb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f3663995cddb48f2989a07d15891bf5e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "4d9e512aa24c4f16a979b2aae359800c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f20b711c4f044879b75087426f938f53": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "### **CLIP-E Contrastive**\n",
        "\n",
        "This notebook demonstrates the inference process using the CLIP-E contrastive model, which was trained to recognize sentiments from input images. The model was trained on the WEBemo dataset\n"
      ],
      "metadata": {
        "id": "HOLfnrnz3wDe"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 1. First, download model weights, test images and dependency libraries"
      ],
      "metadata": {
        "id": "FLXOZJcp5WsQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tN3h5Rhxorvt",
        "outputId": "2648b490-73fc-480d-abcf-9cd895c4327b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting transformers\n",
            "  Downloading transformers-4.33.3-py3-none-any.whl (7.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m55.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.12.2)\n",
            "Collecting huggingface-hub<1.0,>=0.15.1 (from transformers)\n",
            "  Downloading huggingface_hub-0.17.3-py3-none-any.whl (295 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m295.0/295.0 kB\u001b[0m \u001b[31m24.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.23.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.6.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers)\n",
            "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m107.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers)\n",
            "  Downloading safetensors-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m71.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.1)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers) (4.5.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.7.22)\n",
            "Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.17.3 safetensors-0.3.3 tokenizers-0.13.3 transformers-4.33.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# images for testing\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev' -O img_test_1.jpg\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1G6f0_xn4yjik1GhMq4m7-ya_FjFCzQBk' -O img_test_2.jpg"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZIjED5-Z03V6",
        "outputId": "eecc9cf4-8631-426b-f267-a8f7cc0773d8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-10-02 23:08:02--  https://docs.google.com/uc?export=download&id=1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev\n",
            "Resolving docs.google.com (docs.google.com)... 173.194.196.139, 173.194.196.101, 173.194.196.102, ...\n",
            "Connecting to docs.google.com (docs.google.com)|173.194.196.139|:443... connected.\n",
            "HTTP request sent, awaiting response... 303 See Other\n",
            "Location: https://doc-0g-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/fp9gknpfmc4rk5tu2gh6faq9bn4d0or4/1696288050000/03683847712226052473/*/1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev?e=download&uuid=a07b987e-8adb-4ca4-b39b-9cf5067799e0 [following]\n",
            "Warning: wildcards not supported in HTTP.\n",
            "--2023-10-02 23:08:02--  https://doc-0g-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/fp9gknpfmc4rk5tu2gh6faq9bn4d0or4/1696288050000/03683847712226052473/*/1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev?e=download&uuid=a07b987e-8adb-4ca4-b39b-9cf5067799e0\n",
            "Resolving doc-0g-3s-docs.googleusercontent.com (doc-0g-3s-docs.googleusercontent.com)... 108.177.111.132, 2607:f8b0:4001:c07::84\n",
            "Connecting to doc-0g-3s-docs.googleusercontent.com (doc-0g-3s-docs.googleusercontent.com)|108.177.111.132|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 17741 (17K) [image/jpeg]\n",
            "Saving to: ‘img_test_1.jpg’\n",
            "\n",
            "img_test_1.jpg      100%[===================>]  17.33K  --.-KB/s    in 0s      \n",
            "\n",
            "2023-10-02 23:08:02 (75.5 MB/s) - ‘img_test_1.jpg’ saved [17741/17741]\n",
            "\n",
            "--2023-10-02 23:08:02--  https://docs.google.com/uc?export=download&id=1G6f0_xn4yjik1GhMq4m7-ya_FjFCzQBk\n",
            "Resolving docs.google.com (docs.google.com)... 173.194.196.139, 173.194.196.101, 173.194.196.102, ...\n",
            "Connecting to docs.google.com (docs.google.com)|173.194.196.139|:443... connected.\n",
            "HTTP request sent, awaiting response... 303 See Other\n",
            "Location: https://doc-0g-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/stuqkttijpkdnggljvb5o77vh53mrb6s/1696288050000/03683847712226052473/*/1G6f0_xn4yjik1GhMq4m7-ya_FjFCzQBk?e=download&uuid=098d3656-75f0-42b3-a5cd-f93638e7d150 [following]\n",
            "Warning: wildcards not supported in HTTP.\n",
            "--2023-10-02 23:08:03--  https://doc-0g-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/stuqkttijpkdnggljvb5o77vh53mrb6s/1696288050000/03683847712226052473/*/1G6f0_xn4yjik1GhMq4m7-ya_FjFCzQBk?e=download&uuid=098d3656-75f0-42b3-a5cd-f93638e7d150\n",
            "Resolving doc-0g-3s-docs.googleusercontent.com (doc-0g-3s-docs.googleusercontent.com)... 108.177.111.132, 2607:f8b0:4001:c07::84\n",
            "Connecting to doc-0g-3s-docs.googleusercontent.com (doc-0g-3s-docs.googleusercontent.com)|108.177.111.132|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 18319 (18K) [image/jpeg]\n",
            "Saving to: ‘img_test_2.jpg’\n",
            "\n",
            "img_test_2.jpg      100%[===================>]  17.89K  --.-KB/s    in 0s      \n",
            "\n",
            "2023-10-02 23:08:03 (57.5 MB/s) - ‘img_test_2.jpg’ saved [18319/18319]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#model weights\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1qs3yeSW6-hyJ_pCdTtc4tOzwMyntZOgh' -O clip-e_contrastive.hdf5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_wJqoKa-sMfK",
        "outputId": "7b2da5b1-d470-4d4b-cc31-6d9dfc457681"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-10-02 23:08:03--  https://docs.google.com/uc?export=download&id=1qs3yeSW6-hyJ_pCdTtc4tOzwMyntZOgh\n",
            "Resolving docs.google.com (docs.google.com)... 173.194.196.139, 173.194.196.101, 173.194.196.102, ...\n",
            "Connecting to docs.google.com (docs.google.com)|173.194.196.139|:443... connected.\n",
            "HTTP request sent, awaiting response... 303 See Other\n",
            "Location: https://doc-0k-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/0hpqk4piis9a9hq9c91vcp9peb5b1663/1696288050000/03683847712226052473/*/1qs3yeSW6-hyJ_pCdTtc4tOzwMyntZOgh?e=download&uuid=532e22f9-3be3-4855-ae97-9a69be9cbbf1 [following]\n",
            "Warning: wildcards not supported in HTTP.\n",
            "--2023-10-02 23:08:04--  https://doc-0k-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/0hpqk4piis9a9hq9c91vcp9peb5b1663/1696288050000/03683847712226052473/*/1qs3yeSW6-hyJ_pCdTtc4tOzwMyntZOgh?e=download&uuid=532e22f9-3be3-4855-ae97-9a69be9cbbf1\n",
            "Resolving doc-0k-3s-docs.googleusercontent.com (doc-0k-3s-docs.googleusercontent.com)... 108.177.111.132, 2607:f8b0:4001:c07::84\n",
            "Connecting to doc-0k-3s-docs.googleusercontent.com (doc-0k-3s-docs.googleusercontent.com)|108.177.111.132|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 2112800 (2.0M) [application/octet-stream]\n",
            "Saving to: ‘clip-e_contrastive.hdf5’\n",
            "\n",
            "clip-e_contrastive. 100%[===================>]   2.01M  --.-KB/s    in 0.02s   \n",
            "\n",
            "2023-10-02 23:08:04 (105 MB/s) - ‘clip-e_contrastive.hdf5’ saved [2112800/2112800]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2. Imports"
      ],
      "metadata": {
        "id": "a5BO5r5e5zaF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from PIL import Image\n",
        "import tensorflow as tf\n",
        "from transformers import AutoProcessor, AutoTokenizer, TFCLIPModel"
      ],
      "metadata": {
        "id": "uX14KmK8pcfH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 3. CLIP-E contrastive model"
      ],
      "metadata": {
        "id": "0VtdznU-5_YC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def create_vision_encoder():\n",
        "      # Receive the images embeddings as inputs.\n",
        "      FEATURES_SIZE = 512\n",
        "      INPUT_img = tf.keras.layers.Input(shape=(FEATURES_SIZE),name='input_img_features')\n",
        "      x = tf.keras.layers.Dense(512, activation='relu', name='img_fc1')(INPUT_img)\n",
        "      x = tf.keras.layers.Dense(512, activation='linear', name='img_fc2')(x)\n",
        "      img_model = tf.keras.Model(inputs=INPUT_img,outputs=x)\n",
        "      return img_model\n",
        "\n",
        "def create_text_encoder():\n",
        "      # Receive the caption embeddings as inputs.\n",
        "      FEATURES_SIZE = 512\n",
        "      INPUT_text = tf.keras.layers.Input(shape=(FEATURES_SIZE),name='input_text_features')\n",
        "      #after several trials, modyfing the caption embedding space did not have a effect on the model performance, so\n",
        "      #we decided to mantain the clip original embedding for text\n",
        "      #x = tf.keras.layers.Dense(512, activation='relu', name='text_fc1')(INPUT_text)\n",
        "      #x = tf.keras.layers.Dense(512, activation='linear', name='text_fc2')(x)\n",
        "      text_model = tf.keras.Model(inputs=INPUT_text,outputs=INPUT_text)\n",
        "      return text_model\n",
        "\n",
        "\n",
        "class CLIP_E_contrastive(tf.keras.Model):\n",
        "    def __init__(self, text_encoder, vision_encoder, temperature=0.075, **kwargs):\n",
        "        super(CLIP_E_contrastive, self).__init__(**kwargs)\n",
        "        self.text_encoder = text_encoder\n",
        "        self.vision_encoder = vision_encoder\n",
        "        self.temperature = temperature\n",
        "        self.loss_tracker = tf.keras.metrics.Mean(name=\"loss\")\n",
        "\n",
        "    @property\n",
        "    def metrics(self): #this function is for custom training\n",
        "        return [self.loss_tracker]\n",
        "\n",
        "    # Ensure second feature is text and first is image\n",
        "    def call(self, features, training=False):\n",
        "        # Get the embeddings for the captions.\n",
        "        caption_embeddings = text_encoder(features[0], training=training)\n",
        "\n",
        "        # Get the embeddings for the images.\n",
        "        image_embeddings = vision_encoder(features[1], training=training)\n",
        "\n",
        "        return caption_embeddings, image_embeddings\n",
        "\n",
        "\n",
        "    def compute_loss(self, caption_embeddings, image_embeddings):\n",
        "\n",
        "        image_embeddings = image_embeddings / tf.norm(tensor=image_embeddings, ord=\"euclidean\", axis=-1, keepdims=True)\n",
        "        caption_embeddings = caption_embeddings / tf.norm(tensor=caption_embeddings, ord=\"euclidean\", axis=-1, keepdims=True)\n",
        "\n",
        "        # logits[i][j] is the dot_similarity(caption_i, image_j).\n",
        "        logits = (tf.matmul(caption_embeddings, image_embeddings, transpose_b=True) / self.temperature)\n",
        "\n",
        "        # images_similarity[i][j] is the dot_similarity(image_i, image_j).\n",
        "        images_similarity = tf.matmul(image_embeddings, image_embeddings, transpose_b=True)\n",
        "\n",
        "        # captions_similarity[i][j] is the dot_similarity(caption_i, caption_j).\n",
        "        captions_similarity = tf.matmul(caption_embeddings, caption_embeddings, transpose_b=True)\n",
        "\n",
        "        # targets[i][j] = average dot_similarity(caption_i, caption_j) and dot_similarity(image_i, image_j).\n",
        "        targets = tf.keras.activations.softmax((captions_similarity + images_similarity) / (2 * self.temperature))\n",
        "\n",
        "        # Compute the loss for the captions using crossentropy\n",
        "        captions_loss = tf.keras.losses.categorical_crossentropy(y_true=targets, y_pred=logits, from_logits=True)\n",
        "\n",
        "        # Compute the loss for the images using crossentropy\n",
        "        images_loss = tf.keras.losses.categorical_crossentropy(y_true=tf.transpose(targets), y_pred=tf.transpose(logits), from_logits=True)\n",
        "\n",
        "        # Return the mean of the loss over the batch.\n",
        "        return (captions_loss + images_loss) / 2\n",
        "\n",
        "    def train_step(self, features):\n",
        "        with tf.GradientTape() as tape:\n",
        "            # Forward pass\n",
        "            caption_embeddings, image_embeddings = self(features, training=True)\n",
        "            loss = self.compute_loss(caption_embeddings, image_embeddings)\n",
        "\n",
        "        # Backward pass\n",
        "        gradients = tape.gradient(loss, self.trainable_variables)\n",
        "        self.optimizer.apply_gradients(zip(gradients, self.trainable_variables))\n",
        "\n",
        "        # Monitor loss\n",
        "        self.loss_tracker.update_state(loss)\n",
        "        return {\"loss\": self.loss_tracker.result()}\n",
        "\n",
        "    def test_step(self, features):\n",
        "        caption_embeddings, image_embeddings = self(features, training=False)\n",
        "        loss = self.compute_loss(caption_embeddings, image_embeddings)\n",
        "        self.loss_tracker.update_state(loss)\n",
        "        return {\"loss\": self.loss_tracker.result()}"
      ],
      "metadata": {
        "id": "2mZrsZsz6ScL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "3.1 Aux functions for inference"
      ],
      "metadata": {
        "id": "sGIuHArk63U6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from numpy import linalg as LA\n",
        "\n",
        "# Get the position of the most similar text features of an image features\n",
        "# image features contain just one image\n",
        "# list text feature contains a list of text feature for one or more captions\n",
        "def similarity(img_features,list_text_features):\n",
        "  #cosine similarity\n",
        "  img_features /= LA.norm(img_features,axis=-1,keepdims=True)\n",
        "  list_text_features /= LA.norm(list_text_features,axis=-1,keepdims=True)\n",
        "  probs = list_text_features @ img_features.T\n",
        "  probs = tf.nn.softmax(probs).numpy()\n",
        "  final_pred = np.argmax(probs)\n",
        "  return final_pred\n",
        "\n",
        "# Return the cosine similarity of ona single image and a list of captions\n",
        "# image features contain just one image\n",
        "# list text feature contains a list of text feature for one or more captions\n",
        "def similarity_probs(img_features,list_text_features):\n",
        "  img_features /= LA.norm(img_features,axis=-1,keepdims=True)\n",
        "  list_text_features /= LA.norm(list_text_features,axis=-1,keepdims=True)\n",
        "  probs = list_text_features @ img_features.T\n",
        "  probs = tf.nn.softmax(probs).numpy()\n",
        "  return probs\n",
        "\n",
        "# This function was made for testing: the purpose is to create pairs of data, where each pair consists\n",
        "# of a single item from list_text_input_features paired with the same img_input_features\n",
        "# This is because we want to recognize the sentiment of a single image from a list of several sentiment labels\n",
        "def get_pairs(list_text_input_features,img_input_features):\n",
        "  img_input_features = np.tile(img_input_features, (len(list_text_input_features),1))\n",
        "  return (list_text_input_features,img_input_features)"
      ],
      "metadata": {
        "id": "V5oQCxb3CMr5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "3.2  Load original trained CLIP from huggingfaces to extract the image and caption embeddings. Then, CLIP-E contrastive model will be feed with both embeddings"
      ],
      "metadata": {
        "id": "SCO-pIjT9rdC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "clip_model_tf =  TFCLIPModel.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
        "processor = AutoProcessor.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"openai/clip-vit-base-patch32\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362,
          "referenced_widgets": [
            "7546cfc6acbb4e0cbd4bd6829788e57a",
            "b4d943d7667943dd8fd1e408a3a52279",
            "7afe045dcc7c448996c5013e3e622974",
            "fe45fd6fc8e445169a620d616dcf2e22",
            "3c88c87b6d70467cb65f006aab476f2a",
            "c3af5e78a13347dbbe9644a4f1a6f105",
            "898f94dd2f2242a684685b4258019158",
            "2e8cce8884254ae890718ed83d37ecca",
            "a1d51ddcfff849829f12a2a4f3dba3ea",
            "a25fefe1645b4211a312c4de0111b320",
            "2afc0f34505940e88dd9792ccb0bdc50",
            "7e2a19c580444d788fe46680e412d327",
            "b17b630a30424ebbb442c26cc20952c5",
            "30a9bba5a18246239c8ca14b054bc303",
            "d72d87cf51264d34b51942aa6b003a68",
            "6b9eb0faae80483a8741c4faad9a6171",
            "4de0e43af4b143c1bdbc0df06ea96a71",
            "dd631ece54c143998dec7795f7488bf4",
            "49011a6dcc9941999a09ee6ce3ab6959",
            "3323249fd8de42939ed6a9ef32633dce",
            "14c2cd27faab4a58850784701f048726",
            "008e2c6b85534ee18f72997820e075c2",
            "b1cf31daa3eb4fdcb2094a08e68f7410",
            "ee116dc2cf474c6f94e666acec9f4057",
            "00e2937be48f4d9793745ccaa813f2b9",
            "6c22daabed4c483aaf07d92ee94c3c26",
            "8fd80268a2b34249ba4cee9bdba0c3b7",
            "15b05ce1c1434a0c9f23e055f54603f2",
            "3e03bc4ff1664bb8802004c301e018cb",
            "3b6b316b8edf4adb8ea8865c8c09e24b",
            "953fcb8bdb214b009d939c3d17b4c82a",
            "ae6bcc2999d64895b9885f03d626c66e",
            "d6a75fda819e4db5a584479e6746d97c",
            "dfcda88772164b9baa3060bd6a791df2",
            "d7b341c6d2d144288869d7ca9236ece9",
            "290337b217b6484a943c45258789acb1",
            "88bfa71f30084a20ae32077bd0d0dadb",
            "9a2dbcec8fbb4d2dbc0401b06aa6faff",
            "fba2735b9f4742d9ae1c07c930224c57",
            "739788184eb5483dbc146d6fbd7beb2a",
            "490dc51f9c0f4a12941908deaff3e3b0",
            "dc88cfb1726e4671b314797fc911190b",
            "f976b427f2494798ae4c658c0dee5916",
            "633d4a94b7ef4894b80aa3304aa5dcd2",
            "75efa71e777843e8848b88ea5989fdeb",
            "d0c8a50b8da9488d8572f2afaef74845",
            "32fd9d71187a433daa2aef69fbc7812d",
            "aa22f883f356489b8dcc16d080d746d1",
            "7c692a6deab84b2d93731ceed4c18d30",
            "e68733b158154115a6c326ae7d5280c7",
            "2e1289127a324246b79bf1dc598f96de",
            "2b8a81234e2e4763929fc5e7c4663dec",
            "ea4bf1a7c2cc47a193daec0ecbbfa37d",
            "1c4681c44ddd4b599609eceb0daebda8",
            "41d3e17640134324b48236469eba3525",
            "de55938608d04b029d9f93d51e4d8469",
            "b250ea671cfb4606893c58cbd213fb84",
            "dbcf83b0aa4648c49b36dab14b0282cb",
            "42f99a181d924563ad237a524e984d73",
            "49414e423d3e4729971587a5bd78722e",
            "c8c99779d4e9435e80662de03a4e6e8e",
            "0421441fd7eb49c09a6abd97b019ede6",
            "a034afb5fbce44629f32454757ad581a",
            "f555ec3a64024344b2a843fedd247ae3",
            "26d3af4d6f9041928887c8ffff9b1b86",
            "7fe82c4b486b4bafa6b22abdd70dc8d7",
            "020b4b14cddb438d8826a7f4f4b5e57d",
            "a4a2e7380eea4ffaa9ef6b40817167e8",
            "7a936dfe9461481cacea30d3cef7e50f",
            "66c6a9ba5988443e8a36cc1caa51a330",
            "b52fa027a7874e4c8007ad9e78e66cba",
            "711f8ac932d84822be4b53d7b297f7f4",
            "5383e3b1a42242caa0a004f27a7ebf96",
            "dcc077483bd44aca82bd3882d731a8ae",
            "8d1484f2aa8343758e71d748ddedc650",
            "50b2b3ef063a4415b1e02c83c4660c6f",
            "76198e2a893842d4b46d223916f93ec8",
            "4e98f7f6f7e6487db77d66f57e02c7e1",
            "0efc18133e6a4cceb6b2563353677d88",
            "714837a4a3ad4c3386d1acc2e8d56363",
            "129d1b2227b94cbeabccff23398337ce",
            "eeba9e0435534a1ca647ce5240b3aaf7",
            "3a89d19646cb4b0e9b3ec73515701446",
            "650502808486475a9ea393ddbcd95891",
            "46500824ea734f999df671de062437fb",
            "f3663995cddb48f2989a07d15891bf5e",
            "4d9e512aa24c4f16a979b2aae359800c",
            "f20b711c4f044879b75087426f938f53"
          ]
        },
        "id": "xpiXWfcghQ5T",
        "outputId": "fd731124-fb13-4dd0-c5c4-f6cf8274ec39"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/4.19k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7546cfc6acbb4e0cbd4bd6829788e57a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading tf_model.h5:   0%|          | 0.00/606M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7e2a19c580444d788fe46680e412d327"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "All model checkpoint layers were used when initializing TFCLIPModel.\n",
            "\n",
            "All the layers of TFCLIPModel were initialized from the model checkpoint at openai/clip-vit-base-patch32.\n",
            "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFCLIPModel for predictions without further training.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)rocessor_config.json:   0%|          | 0.00/316 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b1cf31daa3eb4fdcb2094a08e68f7410"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/568 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "dfcda88772164b9baa3060bd6a791df2"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/862k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "75efa71e777843e8848b88ea5989fdeb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/525k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "de55938608d04b029d9f93d51e4d8469"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.22M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "020b4b14cddb438d8826a7f4f4b5e57d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/389 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4e98f7f6f7e6487db77d66f57e02c7e1"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4. Inference"
      ],
      "metadata": {
        "id": "1IdbsnFq-i-g"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Taxonomy of sentiments labels to test. This taxonomy is from Parrot emotion model. WEBemo dataset was labeled using this taxonomy.\n",
        "As first experiment, we are going to test using the most fine grained category of 25 sentiments (secondary emotions)"
      ],
      "metadata": {
        "id": "yUtuzXhP-t0z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 25 categories\n",
        "sentiment_labels = ['affection',  'cheerfullness',  'confusion',  'contentment','disappointment', 'disgust','enthrallment','envy',\n",
        "\t        'exasperation','gratitude','horror',  'irritabilty', 'lust','neglect','nervousness','optimism','pride','rage',\n",
        "\t        'relief', 'sadness','shame',  'suffering', 'surprise', 'sympathy', 'zest']"
      ],
      "metadata": {
        "id": "3uxfe0fR_BsS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Visualize the test image"
      ],
      "metadata": {
        "id": "0Exu0WjH_g9s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "img_name = 'img_test_2.jpg'\n",
        "image = Image.open(img_name)\n",
        "image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        },
        "id": "E0dMTOXbhu77",
        "outputId": "c85f53e1-b85e-4027-e842-a064e279aaef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=220x147>"
            ],
            "image/png": "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\n"
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Extract the embeddings from original CLIP model"
      ],
      "metadata": {
        "id": "z-EK56WdAOT2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# get visual embedding\n",
        "inputs = processor(images=image, return_tensors=\"tf\")\n",
        "image_features = clip_model_tf.get_image_features(**inputs)\n",
        "image_features = image_features.numpy()\n",
        "image_features = np.squeeze(image_features)\n",
        "image_features.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G1zMuuaXiMHA",
        "outputId": "653effc2-9b40-49f6-b192-b2d084d048b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(512,)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We create a clip-style sentiment caption for every label from the taxonomy using the following structure \"a photo that evokes $sentiment$\". For example, \"a photo that evokes cheerfullness\""
      ],
      "metadata": {
        "id": "R-ucD2BXAhTP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#get text embeddings\n",
        "text_features = []\n",
        "\n",
        "for sentiment in sentiment_labels:\n",
        "  inputs = tokenizer([\"a photo that evokes \"+sentiment], padding=True, return_tensors=\"tf\")\n",
        "  text_feat_temp = clip_model_tf.get_text_features(**inputs)[0]\n",
        "  text_features.append(text_feat_temp.numpy())\n",
        "\n",
        "text_features = np.asarray(text_features)\n",
        "text_features.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AlujYwMcsH3v",
        "outputId": "59ebb14a-7031-45e9-ade1-fcec32399521"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(25, 512)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Call our trained CLIP-E model 😊😍😭😀😒😡"
      ],
      "metadata": {
        "id": "FrDc0smrBHBT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "vision_encoder = create_vision_encoder()\n",
        "text_encoder = create_text_encoder()\n",
        "model = CLIP_E_contrastive(text_encoder, vision_encoder, temperature=1)\n",
        "model.built = True\n",
        "model.load_weights('clip-e_contrastive.hdf5')"
      ],
      "metadata": {
        "id": "jn6My2J-_kF8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Inference**"
      ],
      "metadata": {
        "id": "6y-IoPVsBxHv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# build pairs of each sentiment text embedding with the same image embedding to match clip-e model input\n",
        "x = get_pairs(text_features,image_features)\n",
        "\n",
        "#inference:\n",
        "text_output,img_output = model.predict(x, verbose=0)\n",
        "\n",
        "img_output = img_output[0] #because all the image outputs correspond to the same image\n",
        "\n",
        "y = similarity(img_output,text_output)"
      ],
      "metadata": {
        "id": "vDvERMhwCnIg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('Sentiment Classification:', sentiment_labels[y])\n",
        "image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 181
        },
        "id": "WJRVrAu1EDFX",
        "outputId": "434a16d8-7377-4f1e-9307-0ce2fc9cb5ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment Classification: contentment\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=220x147>"
            ],
            "image/png": "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\n"
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "It's also interesting to see the top-k predictions"
      ],
      "metadata": {
        "id": "KTr4COtnEfFN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "k = 5\n",
        "y_all_similarities = similarity_probs(img_output,text_output)\n",
        "similarities_ordered = np.sort(y_all_similarities)[::-1]\n",
        "similarities_ordered_index = np.argsort(y_all_similarities)[::-1]\n",
        "sentiment_labels_np = np.asarray(sentiment_labels)\n",
        "top_k_preds = sentiment_labels_np[similarities_ordered_index]\n",
        "\n",
        "print('Top ', k, ' predictions')\n",
        "for i in range(k):\n",
        "  print(str(i+1)+':',top_k_preds[i])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OlTPyJBiET9x",
        "outputId": "610ee06b-d9e0-47f0-ebe6-9f900bcef842"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top  5  predictions\n",
            "1: contentment\n",
            "2: affection\n",
            "3: cheerfullness\n",
            "4: enthrallment\n",
            "5: optimism\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 5. Testing other taxonomies"
      ],
      "metadata": {
        "id": "GbO7MTfRFyU8"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "5.1 Parrot's model primary emotions (6 categories)"
      ],
      "metadata": {
        "id": "0jWSzlBfF5Ed"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sentiment_labels = ['anger', 'fear','joy', 'love', 'sadness', 'surprise']\n",
        "\n",
        "text_features = []\n",
        "for sentiment in sentiment_labels:\n",
        "  inputs = tokenizer([\"a photo that evokes \"+sentiment], padding=True, return_tensors=\"tf\")\n",
        "  text_feat_temp = clip_model_tf.get_text_features(**inputs)[0]\n",
        "  text_features.append(text_feat_temp.numpy())\n",
        "text_features = np.asarray(text_features)\n",
        "\n",
        "# build pairs\n",
        "x = get_pairs(text_features,image_features)\n",
        "#inference:\n",
        "text_output,img_output = model.predict(x, verbose=0)\n",
        "img_output = img_output[0] #because all the image outputs correspond to the same image\n",
        "y = similarity(img_output,text_output)\n",
        "\n",
        "print('Sentiment Classification between 6 categories:', sentiment_labels[y])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7otGRX3lF4M0",
        "outputId": "e505a09e-983b-4456-850d-4dbd18c01e26"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment Classification between 6 categories: love\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "5.2 We can also test using a binary taxonomy. However, for the binary case, we build the captions slightly different: \"a photo that evokes a $sentiment$ feeling\""
      ],
      "metadata": {
        "id": "etdzBVXxHhxq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "binary_sentiment_labels = ['negative', 'positive']\n",
        "\n",
        "text_features = []\n",
        "for sentiment in binary_sentiment_labels:\n",
        "  inputs = tokenizer([\"a photo that evokes a \"+ sentiment +\" feeling\"], padding=True, return_tensors=\"tf\")\n",
        "  text_feat_temp = clip_model_tf.get_text_features(**inputs)[0]\n",
        "  text_features.append(text_feat_temp.numpy())\n",
        "text_features = np.asarray(text_features)\n",
        "\n",
        "# build pairs\n",
        "x = get_pairs(text_features,image_features)\n",
        "#inference:\n",
        "text_output,img_output = model.predict(x, verbose=0)\n",
        "img_output = img_output[0] #because all the image outputs correspond to the same image\n",
        "y = similarity(img_output,text_output)\n",
        "\n",
        "print('Sentiment Classification between binary categories:', binary_sentiment_labels[y])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cQuwEKNHH-Nl",
        "outputId": "826910d1-4297-49bb-835d-88f4241ceede"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment Classification between binary categories: positive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "5.3 Last, testing using the Plutchik emotion wheel categories"
      ],
      "metadata": {
        "id": "bkEcMhl_JkJ0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sentiment_labels = ['amusement', 'anger','awe','contentment','disgust', 'excitement','fear','sadness']\n",
        "\n",
        "text_features = []\n",
        "for sentiment in sentiment_labels:\n",
        "  inputs = tokenizer([\"a photo that evokes \"+sentiment], padding=True, return_tensors=\"tf\")\n",
        "  text_feat_temp = clip_model_tf.get_text_features(**inputs)[0]\n",
        "  text_features.append(text_feat_temp.numpy())\n",
        "text_features = np.asarray(text_features)\n",
        "\n",
        "# build pairs\n",
        "x = get_pairs(text_features,image_features)\n",
        "#inference:\n",
        "text_output,img_output = model.predict(x, verbose=0)\n",
        "img_output = img_output[0] #because all the image outputs correspond to the same image\n",
        "y = similarity(img_output,text_output)\n",
        "\n",
        "print('Sentiment Classification between Plutchik categories:', sentiment_labels[y])\n",
        "image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 181
        },
        "id": "IwR4Pdi8KUfQ",
        "outputId": "7de47e57-8900-4070-be29-3726c5cf3798"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment Classification between Plutchik categories: contentment\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=220x147>"
            ],
            "image/png": "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\n"
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    }
  ]
}